Authors:
Darja Solodovnikova
and
Laila Niedrite
Affiliation:
Faculty of Computing, University of Latvia, Raina blvd. 19, Riga and Latvia
Keyword(s):
Data Warehouse, OLAP, Big Data, Evolution, Adaptation, Architecture.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Architectural Concepts
;
Business Analytics
;
Business Intelligence
;
Change Detection
;
Data Engineering
;
Data Management and Quality
;
Data Warehouse Management
;
Informatics in Control, Automation and Robotics
;
Signal Processing, Sensors, Systems Modeling and Control
;
Software Engineering
Abstract:
The problem of designing data warehouses in accordance with user requirements and adapting its data and schemata to changes in these requirements as well as data sources has been studied by many researchers worldwide in the context of relational database environments. However, due to the emergence of big data technologies and the necessity to perform OLAP analysis over big data, innovative methods must be developed also to support evolution of data warehouse that is used to analyse big data. Therefore, the main objective of this paper is to propose a data warehousing architecture over big data capable of automatically or semi-automatically adapting to user needs and requirements as well as to changes in the underlying data sources.